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Brain subtle anomaly detection based on auto-encoders latent space
  analysis : application to de novo parkinson patients

Brain subtle anomaly detection based on auto-encoders latent space analysis : application to de novo parkinson patients

27 February 2023
Nicolas Pinon
Geoffroy Oudoumanessah
Robin Trombetta
M. Dojat
Florence Forbes
Carole Lartizien
ArXivPDFHTML

Papers citing "Brain subtle anomaly detection based on auto-encoders latent space analysis : application to de novo parkinson patients"

3 / 3 papers shown
Title
GAN-based synthetic FDG PET images from T1 brain MRI can serve to improve performance of deep unsupervised anomaly detection models
GAN-based synthetic FDG PET images from T1 brain MRI can serve to improve performance of deep unsupervised anomaly detection models
Daria Zotova
Nicolas Pinon
Robin Trombetta
R. Bouet
Julien Jung
Carole Lartizien
MedIm
38
0
0
12 May 2025
Evaluation of pseudo-healthy image reconstruction for anomaly detection
  with deep generative models: Application to brain FDG PET
Evaluation of pseudo-healthy image reconstruction for anomaly detection with deep generative models: Application to brain FDG PET
Ravi Hassanaly
Camille Brianceau
Maelys Solal
O. Colliot
Ninon Burgos
MedIm
43
5
0
29 Jan 2024
Towards frugal unsupervised detection of subtle abnormalities in medical
  imaging
Towards frugal unsupervised detection of subtle abnormalities in medical imaging
Geoffroy Oudoumanessah
Carole Lartizien
M. Dojat
Florence Forbes
MedIm
25
2
0
04 Sep 2023
1